水下
人工智能
计算机视觉
计算机科学
图像质量
灰度
色空间
像素
公制(单位)
假彩色
彩色图像
模式识别(心理学)
图像处理
图像(数学)
工程类
地理
考古
运营管理
作者
Miao Yang,Arcot Sowmya
出处
期刊:IEEE transactions on image processing
[Institute of Electrical and Electronics Engineers]
日期:2015-10-19
卷期号:24 (12): 6062-6071
被引量:901
标识
DOI:10.1109/tip.2015.2491020
摘要
Quality evaluation of underwater images is a key goal of underwater video image retrieval and intelligent processing. To date, no metric has been proposed for underwater color image quality evaluation (UCIQE). The special absorption and scattering characteristics of the water medium do not allow direct application of natural color image quality metrics especially to different underwater environments. In this paper, subjective testing for underwater image quality has been organized. The statistical distribution of the underwater image pixels in the CIELab color space related to subjective evaluation indicates the sharpness and colorful factors correlate well with subjective image quality perception. Based on these, a new UCIQE metric, which is a linear combination of chroma, saturation, and contrast, is proposed to quantify the non-uniform color cast, blurring, and low-contrast that characterize underwater engineering and monitoring images. Experiments are conducted to illustrate the performance of the proposed UCIQE metric and its capability to measure the underwater image enhancement results. They show that the proposed metric has comparable performance to the leading natural color image quality metrics and the underwater grayscale image quality metrics available in the literature, and can predict with higher accuracy the relative amount of degradation with similar image content in underwater environments. Importantly, UCIQE is a simple and fast solution for real-time underwater video processing. The effectiveness of the presented measure is also demonstrated by subjective evaluation. The results show better correlation between the UCIQE and the subjective mean opinion score.
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